Before we delve into the details of the unsupervised degradation estimation module (UDEM), we first present the controllable dimensions for real-world interactive modulation.
Recall that we want to investigate the interactive modulation under real-world degradations.
We adopt the high-order degradation process [1]}, [2]} to simulate real-world degradations.
In this setting, there are different degradation types (e.g., Gaussian noise, Poisson noise, anisotropic Gaussian blur) and thus we cannot simply determine the controllable dimensions according to their types.
Furthermore, due to the mixture of different degradation levels
in high-order degradations, the explicit degradation levels can not reflect the actual degradation effects in the corrupted images. For example, a corrupted image is degraded by a sequence of Gaussian blur with \(\sigma _1\) , Gaussian noise, and Gaussian blur with \(\sigma _2\) . We cannot know the final equivalent blur levels on this degraded image.
